Ed Daroza daroza

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JupyterLab 3.3.3 on Binder

JupyterLab 3.2.9 on Binder

Features

Real Time Collaboration enabled

JupyterLab 3.2 on Binder with some extra libraries

##VGG16 model for Keras

This is the Keras model of the 16-layer network used by the VGG team in the ILSVRC-2014 competition.

It has been obtained by directly converting the Caffe model provived by the authors.

Details about the network architecture can be found in the following arXiv paper:

Very Deep Convolutional Networks for Large-Scale Image Recognition

K. Simonyan, A. Zisserman

	import subprocess
	from lib.common.dominoUtil import running_on_local
	from lib.config import PROJECT_PATH
	import time
	import psutil
	import os
	import numpy as np

	def _recommended_threads():
	return psutil.cpu_count()-2

	# Converts the millionbase chess PGN database (http://www.top-5000.nl/pgn.htm) to json
	# with one json dictionary per row. (That is, the resulting file is contain multiple json objects,
	# not just one large).

	import json
	import chess.pgn # From python-chess https://github.com/niklasf/python-chess

	pgn = open("millionbase-2.22.pgn") # Or where you have put it
	fout = open('milionbase-2.22.json', 'w') # Or where you want it

	#!/bin/bash
	#####################################################
	# Name: Bash CheatSheet for Mac OSX
	#
	# A little overlook of the Bash basics
	#
	# Usage:
	#
	# Author: J. Le Coupanec
	# Date: 2014/11/04